Results 211 to 220 of about 101,363 (247)

EEG-based multi-feature fusion assessment for autism

Journal of Clinical Neuroscience, 2018
Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder which affects the developmental trajectory in several behavioral domains, including impairments of social communication, cognitive and language abilities. In this paper, multi-feature fusion method based on EEG signal is used to extract as many as possible features including ...
Jiannan, Kang, Tianyi, Zhou, Junxia, Han, Xiaoli, Li   +3 more
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Alzheimer's Disease Classification Based on Multi-feature Fusion

Current Medical Imaging Formerly Current Medical Imaging Reviews, 2019
Background: In this study, we investigated the fusion of texture and morphometric features as a possible diagnostic biomarker for Alzheimer’s Disease (AD). Methods: In particular, we classified subjects with Alzheimer’s disease, Mild Cognitive Impairment (MCI) and Normal Control (NC) based on texture and morphometric features.
Nuwan, Madusanka, Heung-Kook, Choi, Jae-Hong, So, Boo-Kyeong, Choi   +3 more
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Birdsong classification based on multi-feature fusion

Multimedia Tools and Applications, 2021
The classification of birdsong has very important signification to monitor the bird population in the habitats. Aiming at the birdsong dataset with complex and diverse audio background, this paper attempts to introduce an acoustic feature for voice and music analysis: Chroma.
Na Yan, Aibin Chen, Guoxiong Zhou, Zhiqiang Zhang, Xiangyong Liu, Jianwu Wang, Zhihua Liu, Wenjie Chen   +7 more
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Multi-Features Fusion Based Face Recognition

2017
In order to accelerate data processing and improve classification accuracy, some classic dimension reduction techniques have been proposed in the past few decades, such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Non-negative Matrix Factorization (NMF), etc.
Xianzhong Long, Songcan Chen
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Webpage saliency prediction with multi-features fusion

2016 IEEE International Conference on Image Processing (ICIP), 2016
We proposed a novel model to predict human's visual attention when free-viewing webpages. Compared with natural images, webpages are usually full of salient regions such as logos, text, and faces, while few of them attract human's attention in a short sight. Moreover, webpages perform distinct viewing patterns which are quite different from the natural
Jian Li, Li Su, Bo Wu, Junbiao Pang, Chunfeng Wang, Zhe Wu, Qingming Huang   +6 more
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Hyperspectral image classification using multi-feature fusion

Optics & Laser Technology, 2019
Abstract Traditional hyperspectral image (HSI) classification methods typically use the spectral features and do not make full use of the spatial or other features of the HSI. To address this problem, this paper proposes a novel HSI classification method based on a multi-feature fusion strategy.
Fang Li, Jie Wang, Rushi Lan, Zhenbing Liu, Xiaonan Luo   +4 more
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Multi-feature Late Fusion for Image Tagging

2013 2nd IAPR Asian Conference on Pattern Recognition, 2013
Image tagging plays a critical role in image indexing and retrieval and it has gained more and more attention along with the increasing availability of large quantities of web images. However, most of current tagging methods only utilize single feature type, while combining multiple types of features has been proved to be effective for image analysis ...
Xi Liu, Rujie Liu, Qiong Cao, Fei Li
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Vehicle classification based on multi-feature fusion

5th IET International Conference on Wireless, Mobile and Multimedia Networks (ICWMMN 2013), 2013
In this paper, we focus on the need for vehicle classification based on traffic surveillance videos. In the field of image classification, the representation of images can be realized in two ways, using global features and local features. Many methods using only global features can not cope with occlusion and spatial variations.
null Wenhua Ma, null Qiang Zhang, null Zhenjiang Miao   +2 more
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Multi-feature Fusion for Video Object Tracking

2012 Fifth International Conference on Intelligent Networks and Intelligent Systems, 2012
Tracking by individual features, such as color or motion, is the main reason why most tracking algorithms are not as robust as expected. In order to better describe the object, multi-feature fusion is very necessary. In this paper we introduce a graph grammar based method to fuse the low level features and apply them to object tracking.
Yuqing Song, Dongpeng Yue
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Tiny object detection using multi-feature fusion

MIPPR 2019: Automatic Target Recognition and Navigation, 2020
Vehicle identification is widely used in route planning, safety supervision and military reconnaissance. It is one of the research hotspots of space-based remote sensing applications. Traditional HOG, Gabor features and Hough transform and other manual design features are not suitable for modern city satellite data analysis.
Peng Yang, Yuejin Zhao, Ming Liu, Liquan Dong, Xiaohua Liu, Mei Hui   +5 more
openaire   +1 more source